MA Economics student at the University of Kerala.
My work sits at the intersection of econometrics, statistical inference, and computational research. I am interested in how quantitative methods can be used to investigate empirical questions—and, equally, in how assumptions, model specification, diagnostics, and robustness affect the conclusions we draw from data.
My current work includes empirical economics, simulation-based statistical analysis, time-series methods, regression diagnostics, hierarchical modelling, and likelihood-based inference.
A country-year analysis of the relationship between economic prosperity and human development using data from 1990–2022. The project compares cross-sectional and within-country relationships using OLS, robust inference, two-way fixed effects, diagnostics, and sensitivity analyses.
Methods: panel data · fixed effects · robust inference · model diagnostics · sensitivity analysis
A simulation-based study of what repeated choices under uncertainty can reveal about latent subjective preferences. The analysis combines exploratory methods, clustered inference, logistic regression, hierarchical modelling, maximum-likelihood estimation, structural modelling, and model comparison.
Methods: statistical inference · hierarchical models · maximum likelihood · bootstrap · model comparison
An empirical investigation of market adjustment and mean reversion using long-run data from crude oil, wheat, and copper markets. The project examines how conclusions change when non-stationarity, lag structure, and alternative specifications are taken seriously.
Methods: time-series analysis · stationarity testing · regression · lag analysis · bootstrap
A Monte Carlo study examining how sample size, outliers, multicollinearity, and nonlinearity affect OLS estimation and inference, with comparisons against robust and regularized alternatives.
Methods: Monte Carlo simulation · regression diagnostics · robust regression · regularization
- The Crowding-Out Effect — empirical analysis of government borrowing and private investment using long-run macroeconomic data.
- Does AI Supply Create Its Own Demand? — quantitative analysis of investment and demand relationships in AI infrastructure.
- Statistical inference
- Econometrics and empirical economics
- Computational statistics
- Statistical modelling
- Decision-making under uncertainty
- Reproducible quantitative research
Python · R · SQL
pandas · NumPy · SciPy · statsmodels · scikit-learn · Matplotlib · Jupyter